SARA——一种面向异构无线网络的语义接入点资源分配服务
SARA -- A Semantic Access Point Resource Allocation Service for Heterogenous Wireless Networks
AI总结：
本文提出SARA语义接入点资源分配服务，基于SEANET知识库自动推理并选择异构无线网络中的最佳接入点，实验表明其能提升吞吐量并优于现有算法。
摘要：
在本文中，我们提出了SARA，一种面向异构无线网络的语义接入点（Access Point）资源分配服务，该网络中多种无线接入技术并存。SARA通过自动推理由基于知识的自治网络管理系统——SEANET所提供的全系统知识库，在不同接入技术中选择能够提供最佳服务质量的接入点。基于本体辅助的知识系统SEANET，SARA还能够根据客户定义的规则自动调整接入点选择策略。我们基于具有混合接入技术和不同规模的仿真网络进行评估，结果表明SARA能够明显改善信道状况，具体表现为吞吐量的提升。与当前接入点选择算法的比较表明，SARA优于现有的接入点选择算法。其在时间开销方面的负担是合理的，并且显示出比传统接入点选择方法更快。
英文摘要：
In this paper, we present SARA, a Semantic Access point Resource Allocation service for heterogenous wireless networks with various wireless access technologies existing together. By automatically reasoning on the knowledge base of the full system provided by a knowledge based autonomic network management system -- SEANET, SARA selects the access point providing the best quality of service among the different access technologies. Based on an ontology assisted knowledge based system SEANET, SARA can also adapt the access point selection strategy according to customer defined rules automatically. Results of our evaluation based on emulated networks with hybrid access technologies and various scales show that SARA is able to improve the channel condition, in terms of throughput, evidently. Comparisons with current AP selection algorithms demonstrate that SARA outperforms the existing AP selection algorithms. The overhead in terms of time expense is reasonable and is shown to be faster than traditional access point selection approaches.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
